{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 介绍"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "平台地址：\n",
    "   - http://212.129.136.63/hub/login\n",
    "    \n",
    "查看平台说明及更新文档、提出问题和建议：\n",
    "   - 方法 1：从浏览器进入 Gitee 仓库：https://gitee.com/wandouful/wmby_platform_issues\n",
    "   - 方法 2：进入 http://212.129.136.63/hub/login 平台登陆界面，点击 Help 跳转。\n",
    "\n",
    "如策略用到平台上没有安装的包，请在 Gitee 仓库的 Issues 模块提出，或直接联系我们。\n",
    "\n",
    "请勿下载平台数据。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 一个简单的策略"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "\n",
    "from datetime import date\n",
    "\n",
    "from dateutil.parser import parse\n",
    "import pandas as pd\n",
    "\n",
    "from WMBYPlatform import StrategyPlatform"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 平台初始化（必须）\n",
    "sp = StrategyPlatform()\n",
    "\n",
    "# 设置要回测的品种（必须）\n",
    "# sp.SetStockList(['000001.SZ', '000002.SZ'])  # 仅回测个别股票\n",
    "# 或者\n",
    "sp.SetStockListByCSVFile('ashare.csv')  # 导入回测股票池csv文件，在gitee仓库\"常用股票池\"folder下载文件，上传到平台\n",
    "\n",
    "# 设置回测日期区间（必须），最早支持20100101\n",
    "today = int(date.today().strftime('%Y%m%d'))  # 今日\n",
    "sp.SetDate(20200101, today)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading S_DQ_CLOSE [20200102,20210407]\n"
     ]
    }
   ],
   "source": [
    "### 策略begin\n",
    "\n",
    "# 调取数据按以下格式，两个参数，第一个是\"ashare\"固定参数，代表股票数据，第二个是因子名称，在gitee上有详细的数据字典\n",
    "cps = sp.LoadData('ashare', 'S_DQ_CLOSE')\n",
    "\n",
    "#\n",
    "ma5cps = cps.rolling(5).mean()\n",
    "ma5cps = ma5cps.to_numpy()\n",
    "\n",
    "#\n",
    "ma20cps = cps.rolling(20).mean()\n",
    "ma20cps = ma20cps.to_numpy()\n",
    "\n",
    "# 初始化目标持仓权重矩阵，矩阵大小为 （回测天数*回测股票数）\n",
    "alpha = sp.LoadZeroAlpha()\n",
    "\n",
    "# 填充目标持仓权重矩阵，需注意不要用到未来数据做决策\n",
    "for i in range(1, len(alpha)):  # 索引从1开始，因为第一天（索引0）无法生成持仓\n",
    "    for j in range(len(alpha[0])):\n",
    "        \n",
    "        # 买入五日均线大于20日均线的股票\n",
    "        if ma5cps[i - 1, j] > ma20cps[i - 1, j]:\n",
    "            alpha[i, j] = 1\n",
    "            \n",
    "### 策略end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading S_DQ_CLOSE [20200102,20210407]\n",
      "loading S_DQ_ADJCLOSE [20200102,20210407]\n",
      "loading S_DQ_LOW [20200102,20210407]\n",
      "loading S_DQ_HIGH [20200102,20210407]\n",
      "loading S_DQ_ADJOPEN [20200102,20210407]\n",
      "loading S_DQ_OPEN [20200102,20210407]\n",
      "loading S_DQ_TRADESTATUS_SIG [20200102,20210407]\n",
      "loading S_DQ_PRECLOSE [20200102,20210407]\n",
      "loading S_DQ_ADJPRECLOSE [20200102,20210407]\n",
      "loading S_DQ_AVGPRICE [20200102,20210407]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 304/304 [00:02<00:00, 117.69it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "+------------+------------+------------+------------+------------+------------+------------+----------------+--------------+\n",
      "|  回测收益  |  多头年化  |  基准年化  |  多头夏普  |  最大回撤  |  超额年化  |  超额夏普  |  超额最大回撤  |  日均换手率  |\n",
      "+------------+------------+------------+------------+------------+------------+------------+----------------+--------------+\n",
      "|   9.99%    |   8.02%    |   16.42%   |    0.45    |  -14.18%   |   -8.4%    |   -0.57    |    -27.18%     |    20.01%    |\n",
      "+------------+------------+------------+------------+------------+------------+------------+----------------+--------------+\n"
     ]
    },
    {
     "data": {
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[Date.UTC(2020,11,4,0,0,0,0.0), 0.915901539218408], [Date.UTC(2020,11,7,0,0,0,0.0), 0.9182054608423511], [Date.UTC(2020,11,8,0,0,0,0.0), 0.9153535817100888], [Date.UTC(2020,11,9,0,0,0,0.0), 0.9193554905598489], [Date.UTC(2020,11,10,0,0,0,0.0), 0.9165835365883237], [Date.UTC(2020,11,11,0,0,0,0.0), 0.9223423066606482], [Date.UTC(2020,11,14,0,0,0,0.0), 0.9196166689673584], [Date.UTC(2020,11,15,0,0,0,0.0), 0.9142117380695454], [Date.UTC(2020,11,16,0,0,0,0.0), 0.9141799944742994], [Date.UTC(2020,11,17,0,0,0,0.0), 0.9041804991957987], [Date.UTC(2020,11,18,0,0,0,0.0), 0.9055526848304449], [Date.UTC(2020,11,21,0,0,0,0.0), 0.9019951605236918], [Date.UTC(2020,11,22,0,0,0,0.0), 0.9126294813583014], [Date.UTC(2020,11,23,0,0,0,0.0), 0.9150707391891555], [Date.UTC(2020,11,24,0,0,0,0.0), 0.9197907102963603], [Date.UTC(2020,11,25,0,0,0,0.0), 0.9172010046625649], [Date.UTC(2020,11,28,0,0,0,0.0), 0.9246374880686754], [Date.UTC(2020,11,29,0,0,0,0.0), 0.9085684463569283], [Date.UTC(2020,11,30,0,0,0,0.0), 0.9080232703042006], [Date.UTC(2020,11,31,0,0,0,0.0), 0.9003359209161064], [Date.UTC(2021,0,4,0,0,0,0.0), 0.9003927614967866], [Date.UTC(2021,0,5,0,0,0,0.0), 0.8881845456005291], [Date.UTC(2021,0,6,0,0,0,0.0), 0.8826165455380703], [Date.UTC(2021,0,7,0,0,0,0.0), 0.8706945572513292], [Date.UTC(2021,0,8,0,0,0,0.0), 0.8614238990275647], [Date.UTC(2021,0,11,0,0,0,0.0), 0.86144817033906], [Date.UTC(2021,0,12,0,0,0,0.0), 0.8595244277175511], [Date.UTC(2021,0,13,0,0,0,0.0), 0.8609417329229532], [Date.UTC(2021,0,14,0,0,0,0.0), 0.8604866428108779], [Date.UTC(2021,0,15,0,0,0,0.0), 0.862402415786383], [Date.UTC(2021,0,18,0,0,0,0.0), 0.86125531326419], [Date.UTC(2021,0,19,0,0,0,0.0), 0.8602412731275433], [Date.UTC(2021,0,20,0,0,0,0.0), 0.8558236047079648], [Date.UTC(2021,0,21,0,0,0,0.0), 0.8463217646687755], [Date.UTC(2021,0,22,0,0,0,0.0), 0.8359473183026731], [Date.UTC(2021,0,25,0,0,0,0.0), 0.8244975565579038], [Date.UTC(2021,0,26,0,0,0,0.0), 0.8334876762781847], [Date.UTC(2021,0,27,0,0,0,0.0), 0.830567191567501], [Date.UTC(2021,0,28,0,0,0,0.0), 0.8381865276050608], [Date.UTC(2021,0,29,0,0,0,0.0), 0.8389970088884555], [Date.UTC(2021,1,1,0,0,0,0.0), 0.8375562372690704], [Date.UTC(2021,1,2,0,0,0,0.0), 0.8312846331521404], [Date.UTC(2021,1,3,0,0,0,0.0), 0.8330332647237859], [Date.UTC(2021,1,4,0,0,0,0.0), 0.8325674539310637], [Date.UTC(2021,1,5,0,0,0,0.0), 0.8311853739014115], [Date.UTC(2021,1,8,0,0,0,0.0), 0.8262430242560135], [Date.UTC(2021,1,9,0,0,0,0.0), 0.8175614882925026], [Date.UTC(2021,1,10,0,0,0,0.0), 0.8115634153355666], [Date.UTC(2021,1,18,0,0,0,0.0), 0.8148448677171156], [Date.UTC(2021,1,19,0,0,0,0.0), 0.8151688681329055], [Date.UTC(2021,1,22,0,0,0,0.0), 0.8290401140091119], [Date.UTC(2021,1,23,0,0,0,0.0), 0.8300266269546555], [Date.UTC(2021,1,24,0,0,0,0.0), 0.8429831447277523], [Date.UTC(2021,1,25,0,0,0,0.0), 0.8449779499376053], [Date.UTC(2021,1,26,0,0,0,0.0), 0.8646001075163499], [Date.UTC(2021,2,1,0,0,0,0.0), 0.8614966555580306], [Date.UTC(2021,2,2,0,0,0,0.0), 0.8652377734079344], [Date.UTC(2021,2,3,0,0,0,0.0), 0.8613175904280657], [Date.UTC(2021,2,4,0,0,0,0.0), 0.8778335496680727], [Date.UTC(2021,2,5,0,0,0,0.0), 0.8849922971342292], [Date.UTC(2021,2,8,0,0,0,0.0), 0.9026003968791001], [Date.UTC(2021,2,9,0,0,0,0.0), 0.9089245575374856], [Date.UTC(2021,2,10,0,0,0,0.0), 0.9039547032595721], [Date.UTC(2021,2,11,0,0,0,0.0), 0.8963412713114896], [Date.UTC(2021,2,12,0,0,0,0.0), 0.8988545190389499], [Date.UTC(2021,2,15,0,0,0,0.0), 0.9106969631194051], [Date.UTC(2021,2,16,0,0,0,0.0), 0.9201740394124105], [Date.UTC(2021,2,17,0,0,0,0.0), 0.9133070202207185], [Date.UTC(2021,2,18,0,0,0,0.0), 0.9045502353644721], [Date.UTC(2021,2,19,0,0,0,0.0), 0.9126454199098484], [Date.UTC(2021,2,22,0,0,0,0.0), 0.9124294260774286], [Date.UTC(2021,2,23,0,0,0,0.0), 0.9141655990258057], [Date.UTC(2021,2,24,0,0,0,0.0), 0.9217673725383719], [Date.UTC(2021,2,25,0,0,0,0.0), 0.9135446000943472], [Date.UTC(2021,2,26,0,0,0,0.0), 0.9080001272488676], [Date.UTC(2021,2,29,0,0,0,0.0), 0.9079204103072307], [Date.UTC(2021,2,30,0,0,0,0.0), 0.8938294526260155], [Date.UTC(2021,2,31,0,0,0,0.0), 0.901362458023869], [Date.UTC(2021,3,1,0,0,0,0.0), 0.8920590861848929], [Date.UTC(2021,3,2,0,0,0,0.0), 0.8891640022704446], [Date.UTC(2021,3,6,0,0,0,0.0), 0.8927364084657989], [Date.UTC(2021,3,7,0,0,0,0.0), 0.8954698770508378]], &quot;type&quot;: &quot;line&quot;, &quot;id&quot;: &quot;deri&quot;, &quot;name&quot;: &quot;hedge&quot;, &quot;tooltip&quot;: {&quot;valueDecimals&quot;: 4}}, {&quot;data&quot;: [{&quot;x&quot;: Date.UTC(2020,2,5,0,0,0,0.0), &quot;title&quot;: &quot;H&quot;, &quot;text&quot;: -0.14183102142669035}, {&quot;x&quot;: Date.UTC(2020,3,29,0,0,0,0.0), &quot;title&quot;: &quot;L&quot;, &quot;text&quot;: -0.14183102142669035}], &quot;type&quot;: &quot;flags&quot;, &quot;color&quot;: &quot;green&quot;, &quot;name&quot;: &quot;Series 4&quot;, &quot;onSeries&quot;: &quot;dataseries&quot;}, {&quot;data&quot;: [{&quot;x&quot;: 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      ],
      "text/plain": [
       "<highcharts.highstock.highstock.Highstock at 0x7fd489040750>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 策略效果\n",
    "sp.GeneratePerformanceAshare(alpha)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 进阶操作"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 查看股票因子列表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Description</th>\n",
       "      <th>Memo</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S_DQ_PRECLOSE</td>\n",
       "      <td>昨收盘价(元)</td>\n",
       "      <td>数据保留2位小数</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S_DQ_OPEN</td>\n",
       "      <td>开盘价(元)</td>\n",
       "      <td>数据保留2位小数</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S_DQ_HIGH</td>\n",
       "      <td>最高价(元)</td>\n",
       "      <td>数据保留2位小数</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S_DQ_LOW</td>\n",
       "      <td>最低价(元)</td>\n",
       "      <td>数据保留2位小数</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S_DQ_CLOSE</td>\n",
       "      <td>收盘价(元)</td>\n",
       "      <td>数据保留2位小数</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2781</th>\n",
       "      <td>ASCD_S_EST_BASESHARE_FY2_180DE</td>\n",
       "      <td>预测基准股本综合值</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2782</th>\n",
       "      <td>ASCD_S_EST_BASESHARE_FY3_30D</td>\n",
       "      <td>预测基准股本综合值</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2783</th>\n",
       "      <td>ASCD_S_EST_BASESHARE_FY3_90D</td>\n",
       "      <td>预测基准股本综合值</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2784</th>\n",
       "      <td>ASCD_S_EST_BASESHARE_FY3_180D</td>\n",
       "      <td>预测基准股本综合值</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2785</th>\n",
       "      <td>ASCD_S_EST_BASESHARE_FY3_180DE</td>\n",
       "      <td>预测基准股本综合值</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2786 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                Name Description      Memo\n",
       "0                      S_DQ_PRECLOSE     昨收盘价(元)  数据保留2位小数\n",
       "1                          S_DQ_OPEN      开盘价(元)  数据保留2位小数\n",
       "2                          S_DQ_HIGH      最高价(元)  数据保留2位小数\n",
       "3                           S_DQ_LOW      最低价(元)  数据保留2位小数\n",
       "4                         S_DQ_CLOSE      收盘价(元)  数据保留2位小数\n",
       "...                              ...         ...       ...\n",
       "2781  ASCD_S_EST_BASESHARE_FY2_180DE   预测基准股本综合值       NaN\n",
       "2782    ASCD_S_EST_BASESHARE_FY3_30D   预测基准股本综合值       NaN\n",
       "2783    ASCD_S_EST_BASESHARE_FY3_90D   预测基准股本综合值       NaN\n",
       "2784   ASCD_S_EST_BASESHARE_FY3_180D   预测基准股本综合值       NaN\n",
       "2785  ASCD_S_EST_BASESHARE_FY3_180DE   预测基准股本综合值       NaN\n",
       "\n",
       "[2786 rows x 3 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sp.GetFactorList('ashare')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 查看股票所在行业"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>S_INFO_WINDCODE</th>\n",
       "      <th>S_INFO_NAME</th>\n",
       "      <th>S_INFO_LISTDATE</th>\n",
       "      <th>S_INFO_DELISTDATE</th>\n",
       "      <th>S_INFO_LISTBOARDNAME</th>\n",
       "      <th>INDUSTRIESCODE</th>\n",
       "      <th>INDUSTRIESNAME</th>\n",
       "      <th>LEVELNUM</th>\n",
       "      <th>CUR_SIGN</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>000005.SZ</td>\n",
       "      <td>世纪星源</td>\n",
       "      <td>19901210</td>\n",
       "      <td>None</td>\n",
       "      <td>主板</td>\n",
       "      <td>b104000000</td>\n",
       "      <td>电力及公用事业</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>600656.SH</td>\n",
       "      <td>退市博元(退市)</td>\n",
       "      <td>19901219</td>\n",
       "      <td>20160513</td>\n",
       "      <td>主板</td>\n",
       "      <td>b10d000000</td>\n",
       "      <td>汽车</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>600601.SH</td>\n",
       "      <td>方正科技</td>\n",
       "      <td>19901219</td>\n",
       "      <td>None</td>\n",
       "      <td>主板</td>\n",
       "      <td>b10r000000</td>\n",
       "      <td>计算机</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>600602.SH</td>\n",
       "      <td>云赛智联</td>\n",
       "      <td>19901219</td>\n",
       "      <td>None</td>\n",
       "      <td>主板</td>\n",
       "      <td>b10r000000</td>\n",
       "      <td>计算机</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>600654.SH</td>\n",
       "      <td>ST中安</td>\n",
       "      <td>19901219</td>\n",
       "      <td>None</td>\n",
       "      <td>主板</td>\n",
       "      <td>b10r000000</td>\n",
       "      <td>计算机</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4029</th>\n",
       "      <td>300857.SZ</td>\n",
       "      <td>协创数据</td>\n",
       "      <td>20200727</td>\n",
       "      <td>None</td>\n",
       "      <td>创业板</td>\n",
       "      <td>b10p000000000000</td>\n",
       "      <td>电子</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4030</th>\n",
       "      <td>605188.SH</td>\n",
       "      <td>国光连锁</td>\n",
       "      <td>20200728</td>\n",
       "      <td>None</td>\n",
       "      <td>主板</td>\n",
       "      <td>b10e000000</td>\n",
       "      <td>商贸零售</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4031</th>\n",
       "      <td>688050.SH</td>\n",
       "      <td>爱博医疗</td>\n",
       "      <td>20200729</td>\n",
       "      <td>None</td>\n",
       "      <td>科创板</td>\n",
       "      <td>b10i000000</td>\n",
       "      <td>医药</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4032</th>\n",
       "      <td>605118.SH</td>\n",
       "      <td>力鼎光电</td>\n",
       "      <td>20200730</td>\n",
       "      <td>None</td>\n",
       "      <td>主板</td>\n",
       "      <td>b10p000000000000</td>\n",
       "      <td>电子</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4033</th>\n",
       "      <td>603408.SH</td>\n",
       "      <td>建霖家居</td>\n",
       "      <td>20200730</td>\n",
       "      <td>None</td>\n",
       "      <td>主板</td>\n",
       "      <td>b109000000</td>\n",
       "      <td>轻工制造</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>4034 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     S_INFO_WINDCODE S_INFO_NAME S_INFO_LISTDATE S_INFO_DELISTDATE  \\\n",
       "0          000005.SZ        世纪星源        19901210              None   \n",
       "1          600656.SH    退市博元(退市)        19901219          20160513   \n",
       "2          600601.SH        方正科技        19901219              None   \n",
       "3          600602.SH        云赛智联        19901219              None   \n",
       "4          600654.SH        ST中安        19901219              None   \n",
       "...              ...         ...             ...               ...   \n",
       "4029       300857.SZ        协创数据        20200727              None   \n",
       "4030       605188.SH        国光连锁        20200728              None   \n",
       "4031       688050.SH        爱博医疗        20200729              None   \n",
       "4032       605118.SH        力鼎光电        20200730              None   \n",
       "4033       603408.SH        建霖家居        20200730              None   \n",
       "\n",
       "     S_INFO_LISTBOARDNAME    INDUSTRIESCODE INDUSTRIESNAME  LEVELNUM CUR_SIGN  \n",
       "0                      主板        b104000000        电力及公用事业       2.0        1  \n",
       "1                      主板        b10d000000             汽车       2.0        1  \n",
       "2                      主板        b10r000000            计算机       2.0        1  \n",
       "3                      主板        b10r000000            计算机       2.0        1  \n",
       "4                      主板        b10r000000            计算机       2.0        1  \n",
       "...                   ...               ...            ...       ...      ...  \n",
       "4029                  创业板  b10p000000000000             电子       2.0        1  \n",
       "4030                   主板        b10e000000           商贸零售       2.0        1  \n",
       "4031                  科创板        b10i000000             医药       2.0        1  \n",
       "4032                   主板  b10p000000000000             电子       2.0        1  \n",
       "4033                   主板        b109000000           轻工制造       2.0        1  \n",
       "\n",
       "[4034 rows x 9 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 调取中信一级行业分类，需要等待几秒钟\n",
    "sp.GetAshareAndIndustryInfo()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 股票交易状态因子"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading S_DQ_TRADESTATUS_SIG [20200102,20210407]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>000005.SZ</th>\n",
       "      <th>600656.SH</th>\n",
       "      <th>600601.SH</th>\n",
       "      <th>600602.SH</th>\n",
       "      <th>600654.SH</th>\n",
       "      <th>600652.SH</th>\n",
       "      <th>600651.SH</th>\n",
       "      <th>600653.SH</th>\n",
       "      <th>000004.SZ</th>\n",
       "      <th>000002.SZ</th>\n",
       "      <th>...</th>\n",
       "      <th>688336.SH</th>\n",
       "      <th>688561.SH</th>\n",
       "      <th>300855.SZ</th>\n",
       "      <th>300853.SZ</th>\n",
       "      <th>300858.SZ</th>\n",
       "      <th>300857.SZ</th>\n",
       "      <th>605188.SH</th>\n",
       "      <th>688050.SH</th>\n",
       "      <th>605118.SH</th>\n",
       "      <th>603408.SH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20200102</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20200103</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20200106</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20200107</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20200108</th>\n",
       "      <td>1.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 4034 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          000005.SZ  600656.SH  600601.SH  600602.SH  600654.SH  600652.SH  \\\n",
       "20200102        1.0        NaN        1.0        1.0        1.0        1.0   \n",
       "20200103        1.0        NaN        1.0        1.0        1.0        1.0   \n",
       "20200106        1.0        NaN        1.0        1.0        1.0        1.0   \n",
       "20200107        1.0        NaN        1.0        1.0        1.0        1.0   \n",
       "20200108        1.0        NaN        1.0        1.0        1.0        1.0   \n",
       "\n",
       "          600651.SH  600653.SH  000004.SZ  000002.SZ  ...  688336.SH  \\\n",
       "20200102        1.0        1.0        1.0        1.0  ...        NaN   \n",
       "20200103        1.0        1.0        1.0        1.0  ...        NaN   \n",
       "20200106        1.0        1.0        1.0        1.0  ...        NaN   \n",
       "20200107        1.0        1.0        1.0        1.0  ...        NaN   \n",
       "20200108        1.0        1.0        1.0        1.0  ...        NaN   \n",
       "\n",
       "          688561.SH  300855.SZ  300853.SZ  300858.SZ  300857.SZ  605188.SH  \\\n",
       "20200102        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "20200103        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "20200106        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "20200107        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "20200108        NaN        NaN        NaN        NaN        NaN        NaN   \n",
       "\n",
       "          688050.SH  605118.SH  603408.SH  \n",
       "20200102        NaN        NaN        NaN  \n",
       "20200103        NaN        NaN        NaN  \n",
       "20200106        NaN        NaN        NaN  \n",
       "20200107        NaN        NaN        NaN  \n",
       "20200108        NaN        NaN        NaN  \n",
       "\n",
       "[5 rows x 4034 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 交易状态为1代表可交易, 0/2/NaN代表不可交易。在生成持仓时，可以先剔除无法交易的股票。\n",
    "# 如果alpha中不剔除，sp.GeneratePerformanceAshare也会剔除，但会导致实际选股数少于计划的数量\n",
    "trade_status = sp.LoadData('ashare', 'S_DQ_TRADESTATUS_SIG')\n",
    "trade_status.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 调取指数数据"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading S_DQ_CLOSE [20190102,20210407]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>000905.SH</th>\n",
       "      <th>000300.SH</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>20210331</th>\n",
       "      <td>6254.06934</td>\n",
       "      <td>5048.36084</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20210401</th>\n",
       "      <td>6311.66455</td>\n",
       "      <td>5110.77686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20210402</th>\n",
       "      <td>6326.60596</td>\n",
       "      <td>5161.55713</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20210406</th>\n",
       "      <td>6343.09619</td>\n",
       "      <td>5140.34180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20210407</th>\n",
       "      <td>6348.07617</td>\n",
       "      <td>5103.74268</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           000905.SH   000300.SH\n",
       "20210331  6254.06934  5048.36084\n",
       "20210401  6311.66455  5110.77686\n",
       "20210402  6326.60596  5161.55713\n",
       "20210406  6343.09619  5140.34180\n",
       "20210407  6348.07617  5103.74268"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sp_index = StrategyPlatform()\n",
    "sp_index.SetStockList([\"000905.SH\",\"000300.SH\"])\n",
    "sp_index.SetDate(20190101, today)\n",
    "\n",
    "close_index = sp_index.LoadData(\"aindex\",\"S_DQ_CLOSE\")\n",
    "close_index.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Description</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>S_DQ_LOW</td>\n",
       "      <td>最低价 (点)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>S_DQ_PCTCHANGE</td>\n",
       "      <td>涨跌幅 (%)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>S_DQ_VOLUME</td>\n",
       "      <td>成交量 (手)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>S_DQ_OPEN</td>\n",
       "      <td>开盘价 (点)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>S_DQ_CHANGE</td>\n",
       "      <td>涨跌 (点)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>S_DQ_HIGH</td>\n",
       "      <td>最高价 (点)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>S_DQ_CLOSE</td>\n",
       "      <td>收盘价 (点)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>S_DQ_AMOUNT</td>\n",
       "      <td>成交金额 (千元)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>S_DQ_PRECLOSE</td>\n",
       "      <td>昨收盘价 (点)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Name Description\n",
       "0        S_DQ_LOW     最低价 (点)\n",
       "1  S_DQ_PCTCHANGE     涨跌幅 (%)\n",
       "2     S_DQ_VOLUME     成交量 (手)\n",
       "3       S_DQ_OPEN     开盘价 (点)\n",
       "4     S_DQ_CHANGE      涨跌 (点)\n",
       "5       S_DQ_HIGH     最高价 (点)\n",
       "6      S_DQ_CLOSE     收盘价 (点)\n",
       "7     S_DQ_AMOUNT   成交金额 (千元)\n",
       "8   S_DQ_PRECLOSE    昨收盘价 (点)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 查看指数可用因子\n",
    "sp_index.GetFactorList('aindex')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 使用向量化运算代替for循环\n",
    "\n",
    "向量化运算能够提升程序的效率，缩短运行时间。\n",
    "\n",
    "可以在互联网上搜索“python 向量化运算”，或参考pandas和numpy文档。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading S_DFA_EBITDA_TTM [20200102,20210407]\n",
      "loading S_DFA_OP_TTM [20200102,20210407]\n"
     ]
    }
   ],
   "source": [
    "ebitda = sp.LoadData(\"ashare\", 'S_DFA_EBITDA_TTM')\n",
    "op = sp.LoadData(\"ashare\", 'S_DFA_OP_TTM')\n",
    "ebitda.fillna(method='ffill', inplace=True)  # 向前填充缺失值\n",
    "alpha2 = sp.LoadZeroAlpha()\n",
    "\n",
    "for i in range(1,len(alpha2)):\n",
    "    # 买入 ebitda 值大于 95% 分位数的股票，然后在被选择的股票中以op因子值的rank作为权重\n",
    "    # 此处没有对每个股票做循环，而是对整行进行计算\n",
    "    selected = (ebitda.iloc[i-1, :] > ebitda.iloc[i-1, :].quantile(0.95)).to_numpy()\n",
    "    alpha2[i, selected] = op.iloc[i-1, selected].rank()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 自定义调仓序列"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "rebalance_series = sp.LoadRebalanceSeries() # 初始化，值为 1 的 pd.Series，代表每天调仓\n",
    "date_num_list  = sp.GetTradeDateList()\n",
    "date_list = [parse(str(d)) for d in date_num_list]\n",
    "\n",
    "# 每周一调仓\n",
    "for i in range(len(date_list)):\n",
    "    if date_list[i].weekday() < date_list[i-1].weekday():\n",
    "        rebalance_series.iloc[i] = 1 # 周初换仓，1代表换仓，0代表维持前一交易日的仓位\n",
    "    else :\n",
    "        rebalance_series.iloc[i] = 0\n",
    "\n",
    "# 月初调仓\n",
    "# for i in range(len(date_list)):\n",
    "#     if date_list[i].month != date_list[i-1].month:\n",
    "#         rebalance_series.iloc[i] = 1\n",
    "#     else :\n",
    "#         rebalance_series.iloc[i] = 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 调整回测参数"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "loading S_DQ_CLOSE [20200102,20210407]\n",
      "loading S_DQ_ADJCLOSE [20200102,20210407]\n",
      "loading S_DQ_LOW [20200102,20210407]\n",
      "loading S_DQ_HIGH [20200102,20210407]\n",
      "loading S_DQ_ADJOPEN [20200102,20210407]\n",
      "loading S_DQ_OPEN [20200102,20210407]\n",
      "loading S_DQ_TRADESTATUS_SIG [20200102,20210407]\n",
      "loading S_DQ_PRECLOSE [20200102,20210407]\n",
      "loading S_DQ_ADJPRECLOSE [20200102,20210407]\n",
      "loading S_DQ_AVGPRICE [20200102,20210407]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "100%|██████████| 304/304 [00:00<00:00, 327.83it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "历史平均风格分布：\n",
      "+----------+----------+----------+----------+\n",
      "|          |  大市值  |  中市值  |  小市值  |\n",
      "+----------+----------+----------+----------+\n",
      "|  价值型  |  61.46%  |  13.78%  |  0.12%   |\n",
      "|  混合型  |  13.89%  |  0.47%   |  0.04%   |\n",
      "|  成长型  |  9.37%   |  0.85%   |   0.0%   |\n",
      "+----------+----------+----------+----------+\n",
      "\n",
      "最新持仓风格分布：\n",
      "+----------+----------+----------+----------+\n",
      "|          |  大市值  |  中市值  |  小市值  |\n",
      "+----------+----------+----------+----------+\n",
      "|  价值型  |  63.09%  |  12.52%  |   0.0%   |\n",
      "|  混合型  |  15.08%  |  0.35%   |  0.14%   |\n",
      "|  成长型  |  8.48%   |  0.34%   |   0.0%   |\n",
      "+----------+----------+----------+----------+\n",
      "\n",
      "+------------+------------+------------+------------+------------+------------+------------+----------------+--------------+\n",
      "|  回测收益  |  多头年化  |  基准年化  |  多头夏普  |  最大回撤  |  超额年化  |  超额夏普  |  超额最大回撤  |  日均换手率  |\n",
      "+------------+------------+------------+------------+------------+------------+------------+----------------+--------------+\n",
      "|   18.38%   |   14.76%   |   16.42%   |    0.74    |  -15.88%   |   -1.66%   |   -0.13    |    -17.69%     |    1.38%     |\n",
      "+------------+------------+------------+------------+------------+------------+------------+----------------+--------------+\n"
     ]
    },
    {
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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "'''\n",
    "alpha: 目标权重持仓表\n",
    "limit_days：新股上市后N天不可交易，默认60个交易日\n",
    "cost: 交易手续费率，默认单边万分之八即0.0008，双边收取\n",
    "cash_init：初始金额，默认1000万\n",
    "benchmark: 所使用的基准，默认\"ZZ500\"中证500,\n",
    "           也可填\"HS300\"沪深300, \"SZZZ\"上证综指, \"SZ50\"上证50, \"CYBZ\"创业板指；\n",
    "           也可填中信一级行业名称（例如 benchmark=\"轻工制造\"），即以该中信行业指数为基准\n",
    "mode: 0-单利计算（默认），1-复利计算\n",
    "deal: \"open\" 或 \"vwap\" 或 \"preclose\"\n",
    "display: 是否导出持仓净值等信息到performance文件夹。默认False\n",
    "rebalance_series: 调仓序列，默认为None即每天调仓。若不为None, 序列中1代表调仓，为0表示按上个交易日持仓\n",
    "backtest_start_date: 回测显示开始日期，默认为SetDate中设定的起始日期\n",
    "analyze_style: 是否分析大小盘和成长/价值风格，默认False\n",
    "analyze_industry: 是否分析行业分布，默认False\n",
    "'''\n",
    "\n",
    "sp.GeneratePerformanceAshare(\n",
    "    alpha2,\n",
    "    limit_days=90,\n",
    "    cost=0.0008,\n",
    "    cash_init=1000 * 10000,\n",
    "    benchmark=\"ZZ500\",\n",
    "    mode=0,\n",
    "    deal=\"open\",\n",
    "    display=False,\n",
    "    rebalance_series=rebalance_series,\n",
    "    backtest_start_date=None,\n",
    "    analyze_style=True,\n",
    "    analyze_industry=True\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.5"
  },
  "toc": {
   "base_numbering": 1,
   "nav_menu": {},
   "number_sections": true,
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   "skip_h1_title": false,
   "title_cell": "Table of Contents",
   "title_sidebar": "Contents",
   "toc_cell": false,
   "toc_position": {
    "height": "calc(100% - 180px)",
    "left": "10px",
    "top": "150px",
    "width": "165px"
   },
   "toc_section_display": true,
   "toc_window_display": true
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
